Tilthq

Staff Data Scientist, Cashalo

Melbourne, Victoria, AustraliaRemoteFull timeStaffPosted 14 days ago
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JOIN THE TILT TEAM

At Tilt, we see a side of people that traditional lenders miss. Our mobile-first products and machine learning-powered credit models look beyond credit scores, using over 250 real-time financial signals to recognize real potential. With millions of customers worldwide, we're not just changing how people access financial products — we're creating a new credit system that backs the working, whatever they're working toward.

THE OPPORTUNITY: STAFF DATA SCIENTIST

We’re hiring for a Staff Data Scientist to help expand Tilt’s credit modeling and risk analytics capability for our Philippines-based business, Cashalo.

This is a high impact role with a direct mandate to build and refine underwriting models as well as other models, working at the intersection of credit, data science, and leadership.

You’ll collaborate with a lean but growing team, applying advanced modeling techniques to predict loss performance, leverage alternative data sources, and build next-generation tools that shape credit access for millions.

This is a 100% remote role that requires travel 2-4 times/year.

HOW YOU'LL MAKE AN IMPACT

- Cashalo is undertaking a solid turn in unit economics with a view to growing to being the largest fintech in PH, and this is an opportunity to build foundational credit models and features from the ground up.

- With direct exposure to leadership, your work will shape both near-term lending performance and long-term data infrastructure.

- You will partner directly with cross-functional teams across credit, engineering, and leadership, bringing strong project and stakeholder management skills to a lean, fast-growing team.

- Work with alternative data where the underwriting process and modeling reflect the maturity of the market

WHY YOU'RE A GREAT FIT

- Deep expertise in predictive modeling, ideally within credit risk or actuarial settings.

- Strong proficiency in Python, SQL, and ML libraries like scikit-learn, LightGBM, XGBoo...